Sensor Metadata

This data set comprises half hourly water level, temperature, and conductivity data aggregated to the 5 min interval from two Onset Hobo U20L-04 pressure transducers (one measuring water pressure and one measuring air pressure) and one Hobo U24-001 Conductivity sensor which also measures temperature. The sensors were installed in 2017 and are typically downloaded twice per year.

This data set contains 1058805 measurements from 20-10-22 to 2023-10-12 see table 2 for a proportional breakdown of data set quality levels.

Date Comment
2017-05-20 Conductivity (SC) sensor installed
2017-08-31 Water level (PT) installed
2017-12 PT froze and clogged with sediment ~Dec 2017; data compromised intermittently
2018-05 Installation and sensors removed; sensors malfunctioned
2018-07 Sensors re-installed; new PT2 sensor installed for overlap
2018-10 PT uninstalled; PT2 continues to operate
2021-05-11 SC sensor malfunction; removed indefinitely
2021-10-22 PT2 download; re-installed upside down
2021-10-22 11cm offset added to account for vertical change - average of height diff; sensor length = 15.74cm; sensor position = 15.74 - 1.6 cm;new sensor height = 13.72 cm
2022-03-21 PT2 re-installed in correct position; offset removed
2022-10-18 PT2 downloaded
2023-04-08 PT2 downloaded

QC methods

The following depicts the typical methodology applied to create the stream stage, and temperature time-series data package which uses 5-minute average measurements that are quality controlled (QC’d), flagged and corrected where needed (Table 1-4) outlined below:

  1. Download annual data
  2. Check for outliers
  3. Check for prevalence of automated flags
  4. Range – Confirm data fall within realistic upper and lower bounds (i.e typically no sub-zero temperatures in summer months depending on elevation of site)
  5. Persistence – Is there a repeated value indicative of a sensor malfunction?
  6. Internal consistency – Are values realistic for a given time period? (i.e does water temperature fluctuate diurnally?)
  7. Spatial consistency – Are data patterns consistent with what networked sensors in the same area recorded?
  8. Manual gap-filling – Use linear regression to establish relationship between two sensors and compute missing values for gap-filling
  9. Assign flags to remaining data in accordance with “Hakai Sensor Network Quality Control (QC)” document
  10. Re-upload to Sensor Network QC portal
Table 1. Quality control flag count summary for the Koeye River Station.
sensor qflag count
PT AV 24954
PT EV 53983
PT SVC 22573
PT2 AV 278813
PT2 EV 89484
PT2 SVC 10553
SC AV 77881
tempPT AV 101469
tempPT2 AV 317953
tempPT2 SVC 2830
tempPT2 SVD 7
tempSC AV 78305

Annual Data

2017
2018
2019
2020
2021
2022
2023